K-means Clustering Using R A Case Study of Market Segmentation

被引：5
作者：
Phan Duy Hung [1 ]
Nguyen Duc Ngoc [1 ]
Tran Duc Hanh [1 ]
机构：
[1] FPT Univ, Hanoi, Vietnam
来源：
PROCEEDINGS OF THE 2019 5TH INTERNATIONAL CONFERENCE ON E-BUSINESS AND APPLICATIONS (ICEBA 2019) | 2019年
关键词：
Market segmentation; Clustering; K-means; Black Friday; Machine learning; RESPIRATORY WAVE-FORM;
D O I：
10.1145/3317614.3317626
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
In recent years, machine learning is widely used to support human decision making in several related scientific areas such as medical, biological, image processing and so on. However in market classification, marketing segmentation is facing numerous challenges in defining specific target customer zones to help enterprises launching their marketing strategies. On the other hand, modem technologies and programming languages are providing support for statistical estimations and graphic visualizations, especially in the R language. In this paper, a k-means machine learning (ML) algorithm with an R language implementation is utilized for marketing segmentation in a specific case study of Black Friday for determining potential customer zones to make reasonable marketing strategies.
引用
收藏
页码：100 / 104
页数：5
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